Method and apparatus for feedback in 3D MIMO wireless systems

ABSTRACT

Systems and methods provide channel state information feedback in a multiple-input multiple-output (MIMO) system. A method quantizes a pre-coding matrix indicator (PMI) and feeds it back from a user equipment (UE) to an evolved Node B (eNodeB). The method may use codebooks for vector quantization of optimal horizontal direction and a scalar quantizer to quantize an optimal vertical direction from the eNodeB to a selected UE.

RELATED APPLICATION

This application claims the benefit under 35 U.S.C. §119(e) of U.S.Provisional Application No. 61/676,775, filed Jul. 27, 2012, which ishereby incorporated by reference herein in its entirety.

TECHNICAL FIELD

This disclosure relates to wireless communication networks.Specifically, this disclosure relates to systems and methods forproviding channel state information feedback in a multiple-inputmultiple-output system.

BACKGROUND

In wireless communication systems, multiple-input multiple-output (MIMO)technology is used to increase transmission capacity and quality. MIMOtechnology may find use in a variety of applications including, forexample, 3G and 4G systems, such as in third generation partnershipproject (3GPP) long term evolution (LTE) networks and/or LTE-Advancednetworks, the Institute of Electrical and Electronics Engineers (IEEE)802.16 standard (e.g., 802.16p), which is commonly known to industrygroups as WiMAX (Worldwide interoperability for Microwave Access), andthe IEEE 802.11 standard, which is commonly known to industry groups asWiFi. In 3GPP radio access networks (RANs) in LTE systems, thetransmission station can be a combination of Evolved UniversalTerrestrial Radio Access Network (E-UTRAN) Node Bs (also commonlydenoted as evolved Node Bs, enhanced Node Bs, eNodeBs, or eNodeBs) andRadio Network Controllers (RNCs) in an E-UTRAN, which communicates withthe wireless mobile device, known as a user equipment (UE).

To achieve better spatial multiplexing with a high transmission rate, atransmitter (e.g., at an access point or base station such as an eNodeB)performs beamforming and power allocation according to channel state. Areceiver (e.g., at user's mobile phone or other UE) measures channelstate information (CSI) and provides feedback to the transmitter. TheCSI of a MIMO system may be represented by a matrix having a pluralityof complex elements. Based on the number of antennas and users, the CSImatrix may be very large. To reduce the overhead of the uplink channel,some wireless systems use a codebook-based pre-coding method where theUE selects a pre-coding matrix from a codebook according to the measuredCSI matrix, and feeds back an index corresponding to the selectedpre-coding matrix to the eNodeB. The eNodeB then obtains the pre-codingmatrix by looking up the codebook according to the index, and pre-codesdata to be transmitted using this pre-coding matrix (e.g., insingle-user MIMO) or a newly calculated pre-coding matrix based on thepre-coding matrices received from multiple UEs (e.g., in multi-userMIMO).

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of a mobile communication system applyinghorizontal beamforming to transmit a beam at a fixed vertical angle.

FIG. 2 is a block diagram of a mobile communication system applyingthree-dimensional beamforming according to certain embodiments.

FIG. 3 schematically illustrates a two-dimensional antenna arrayaccording to one embodiment.

FIG. 4 is a block diagram of the two-dimensional antenna array shown inFIG. 3 illustrating respective phase shifting according to oneembodiment.

FIG. 5 schematically illustrates steering a beam in three dimensionswith the two-dimensional antenna array shown in FIG. 3 according to oneembodiment.

FIG. 6 is a simplified block diagram of a wireless MIMO system withthree-dimensional beamforming according to one embodiment.

FIG. 7 is a flowchart of a method for channel information feedback in aMIMO network with three-dimensional beamforming according to oneembodiment.

FIG. 8 is a flowchart of a method for three-dimensional beamforming in atransmitter station with a two-dimensional antenna array according toone embodiment.

FIG. 9 illustrates an example user equipment that may be used withcertain embodiments disclosed herein.

DETAILED DESCRIPTION

A detailed description of systems and methods consistent withembodiments of the present disclosure is provided below. While severalembodiments are described, it should be understood that disclosure isnot limited to any one embodiment, but instead encompasses numerousalternatives, modifications, and equivalents. In addition, whilenumerous specific details are set forth in the following description inorder to provide a thorough understanding of the embodiments disclosedherein, some embodiments can be practiced without some or all of thesedetails. Moreover, for the purpose of clarity, certain technicalmaterial that is known in the related art has not been described indetail in order to avoid unnecessarily obscuring the disclosure.

As discussed above, a base station such as an eNodeB in a MIMO systemmay achieve better spatial multiplexing with a high transmission rate byperforming beamforming and power allocation according to channel state.While a one-dimensional (1D) antenna array may be used for horizontalbeamsteering, many systems using a 1D antenna array transmit radiofrequency (RF) beams at a fixed vertical angle. For example, FIG. 1 is ablock diagram of a mobile communication system 100 applying horizontalbeamforming to transmit an RF beam 110 from an eNodeB 112 at a fixedvertical angle that is common across a cell 114 and is notuser-specific. As illustrated in FIG. 1, this causes a reduction inreceived signal power at an intended UE 116 when the actual verticalangle from the eNodeB 112 to that UE 116 is different from the verticaltilting angle of the RF beam 110 used by the eNodeB 112. Moreover, usinga 1D antenna array (not shown), the eNodeB 112 may not be able tominimize intra-cell and inter-cell interferences. Thus, the signalleakage to other UEs 118, 120, 122 in the system may be relativelylarge.

System throughput may be increased and performance improved by usingthree-dimensional (3D) beamforming where a two-dimensional (2D) antennaarray steers one or more transmit RF beams in both horizontal andvertical directions. Thus, 3D beamforming provides user-specificvertical tilting to the system to increase received signal power andreduce interference to other users.

For example, FIG. 2 is a block diagram of a mobile communication system200 applying 3D beamforming according to certain embodiments. In FIG. 2,an eNodeB 212 within a cell 214 steers a first RF beam 210 to a first UE216 and a second RF beam 213 to a second UE 218. Skilled persons willrecognize from the disclosure herein that the eNodeB 212 may beconfigured to transmit a single RF beam at a time or more than the twoRF beams 210, 213 at a time. For example, the eNodeB 212 may beconfigured to simultaneously transmit RF beams to each of a plurality ofUEs 216, 218, 220, 222 within the cell 214. FIG. 2 shows an example inwhich different vertical tiltings are used depending on the position ofthe UEs 216, 218 relative to the eNodeB 212.

However, one challenge in communication systems with 3D beamforming isthe large amount of CSI data that needs to be fed back from the UEs 216,218 to the eNodeB 212. This is due to the use of a 2D antenna array (notshown) with a relatively large number of antennas that is required atthe eNodeB 212 to enable beamforming in both horizontal and verticaldirections. In certain embodiments, for example, the eNodeB 212 sends apilot signal or reference signal for each antenna in the antenna array.The UEs 216, 218, knowing the characteristics and parameters of thereference signals ahead of time, use the reference signals to estimatethe respective channels from the eNodeB 212. Thus, increasing the numberof antennas increases the amount of CSI data and the feedback overhead,as compared to conventional systems that use only a 1D antenna array.The inventors of the present application have recognized that newcodebooks are needed for vector quantization in such systems.

Thus, a method is disclosed herein to quantize a pre-coding matrixindicator (PMI) and feed it back from a UE to an eNodeB. In certainembodiments, the method utilizes LTE codebooks for vector quantizationof optimal horizontal direction and a scalar quantizer to quantize theoptimal vertical direction to a selected UE.

FIG. 3 schematically illustrates a 2D antenna array 300 arranged withrespect to an x-axis, a y-axis, and a z-axis according to oneembodiment. For illustrative purposes, a vector 306 corresponding to anRF beam direction is shown at a vertical angle θ with respect to thez-axis. A projection 308 of the vector 306 is shown in the x-y plane toillustrate that the vector 306 is pointing at a horizontal angle φ withrespect to the x-axis.

The 2D antenna array 300 includes N_(H) horizontal and N_(V) verticalantenna elements 310 respectively separated in the horizontal direction(e.g., the x-direction) by distance d_(H) and in the vertical direction(e.g., the z-direction) by distance d_(V). In this example, N_(H)=5antenna elements 310 and N_(V)=5 antenna elements 310. Skilled personswill recognize, however, that any number of antenna elements may be usedin either direction to form a 2D array and that N_(H) and N_(V) do notnecessarily need to be equal. In certain embodiments, the antennaelements 310 in one row can be both co-polarized and cross-polarized.

Under these assumptions, the overall RF beam transmitted by the 2Dantenna array 300 can be selectively pointed to a vertical angle θ₀(shown in FIG. 5) by introducing respective phase shifts to verticalantennas n_(v)=1, 2, . . . , N_(V). For example, FIG. 4 is a blockdiagram of the 2D antenna array 300 shown in FIG. 3 illustratingrespective phase shifting 410 applied to the antenna elements 310 (Ant)according to one embodiment.

In column 1, the phase terms applied to the RF signal input to theantenna elements 310 of each row are:

${{Row}\mspace{14mu} 1\text{:}\mspace{14mu} w_{1}},{{Row}\mspace{14mu} 2\text{:}\;{\mathbb{e}}^{{- j}\frac{2\pi}{\lambda}d_{v}\cos\;\theta_{0}}w_{1}}\mspace{11mu},\ldots$${Row}\mspace{14mu} N_{V}\text{:}\mspace{14mu}{\mathbb{e}}^{{- {j{({N_{V} - 1})}}}\frac{2\pi}{\lambda}d_{v}\cos\;\theta_{0}}{w_{1}.}$where w₁ is a coefficient of the transmission channel corresponding tocolumn 1, and λ is the wavelength of the RF signal.

Each of the column of antenna elements 310 applies a respectivecoefficient of linear transmit antenna weight (e.g., column 1 uses w₁,column 2 uses w₂, . . . , column N_(H) uses w_(N) _(H) ). Thus, incolumn N_(H), the phase terms applied to the RF signal input to theantenna elements 310 of each row are:

${{Row}\mspace{14mu} 1\text{:}\mspace{14mu} w_{N_{H}}},{{Row}\mspace{14mu} 2\text{:}\mspace{14mu}{\mathbb{e}}^{{- j}\frac{2\;\pi}{\lambda}d_{v}\cos\;\theta_{0}}w_{N_{H}}},\ldots$${Row}\mspace{14mu} N_{V}\text{:}\mspace{14mu}{\mathbb{e}}^{{- {j{({N_{V} - 1})}}}\frac{2\pi}{\lambda}d_{v}\cos\;\theta_{0}}{w_{N_{H}}.}$

As shown in FIG. 5, the phase shifting of FIG. 4 results in steering anRF beam 510 horizontally based on the coefficients of linear transmitantenna weights w₁, w₂, . . . , w_(N) _(H) , and vertically based on theparameter θ₀.

FIG. 6 is a simplified block diagram of a wireless MIMO system 600 with3D beamforming according to one embodiment. The system 600 includes aneNodeB 610 and a UE 611. The eNodeB 610 includes circuitry for aprecoder/transmitter 612, a PMI reconstructor 614, a vector dequantizer616, and a scalar dequantizer 618. The UE 611 includes circuitry for areceiver/channel estimator 620, a PMI module 622, a vector quantizer624, and a scalar quantizer 624.

The precoder/transmitter 612 of the eNodeB 610 is configured to transmitreference signals 628 to the UE 611. As discussed above, theprecoder/transmitter 612 may transmit a reference signal for eachantenna in a 2D antenna array (not shown) of the eNodeB 610, or for asubset of the antenna in the 2D antenna array. The receiver/channelestimator 620 of the UE 611 receives the references signals 628 andestimates an N_(H)N_(V)×N_(r) channel represented by a channel matrix Hbased on the received reference signals 628. N_(H) is the number oftransmit horizontal antennas in the eNodeB's 2D antenna array, N_(V) isthe number of transmit vertical antennas in the eNodeB's 2D antennaarray, and N_(r) the number of receive antennas at the UE 611.

The receiver/channel estimator 620 provides the estimated channel matrixH to the PMI module 622. The PMI module 622 processes the estimatedchannel matrix H to calculate one or more PMI vectors and estimatevalues for w₁, w₂, . . . , w_(N) _(H) and d_(v) cos θ₀. The PMI module622 may calculate the PMI vectors using a number of different methods.In one embodiment, for example, the PMI module 622 performs singularvalue decomposition (SVD) on the channel matrix H and finds the rdominant eigenvectors, where “r” is the transmission rank. In certainsuch embodiments, the r-th eigenvectors are in the form:v _(r) =[v _(r,1) , . . . ,v _(r,N) _(H) _(N) _(V) ]^(T),where “T” denotes matrix transpose.

Conventional systems with base stations that transmit downlink signalsusing a 1D antenna array may use a PMI vector of the form:u(w ₁ , . . . ,w _(N) _(H) )=[w ₁ ,w ₂ , . . . ,w _(N) _(H) ]^(T).

However, certain embodiments disclosed herein use a PMI vector thataccounts for the 2D antenna array of the eNodeB 610, and which is of theform:

${u\left( {w_{1},\ldots\mspace{14mu},{w_{N_{H},}\theta_{0}}} \right)} = {\begin{bmatrix}{w_{1},\ldots\mspace{14mu},{w_{N_{H},}{\mathbb{e}}^{j\frac{2\;\pi}{\lambda}d_{v}\cos\;\theta_{0}}w_{1}},\ldots\mspace{14mu},{{\mathbb{e}}^{j\frac{2\;\pi}{\lambda}d_{v}\cos\;\theta_{0}}w_{N_{H}}},\ldots\mspace{14mu},} \\{{{\mathbb{e}}^{{j{({N_{V} - 1})}}\frac{2\pi}{\lambda}d_{v}\cos\;\theta_{0}}w_{1}},\ldots\mspace{14mu},{{\mathbb{e}}^{{j{({N_{V} - 1})}}\frac{2\pi}{\lambda}d_{v}\cos\;\theta_{0}}w_{N_{H}}}}\end{bmatrix}^{T}.}$

To find optimal values for w₁, . . . , w_(N) _(H) , θ₀, the PMI module622 solves the non-linear least square (LS) problem:

$\min\limits_{w_{1},\ldots\mspace{14mu},{w_{N_{H},}\theta_{0}}}{{{v_{r} - {u\left( {w_{1},\ldots\mspace{14mu},{w_{N_{H},}\theta_{0}}} \right)}}}^{2}.}$

This LS problem may be solved using any LS problem solution. In oneembodiment, for example, the LS problem is solved as follows:

${\min\limits_{w_{1},\ldots\mspace{14mu},{w_{N_{H},}\theta_{0}}}{{{\ln\left( v_{r} \right)} - {Az}}}^{2}},{A = \begin{bmatrix}1 & 0 & 0 & \ldots & 0 & 0 \\0 & 1 & 0 & \ldots & 0 & 0 \\\vdots & \vdots & \vdots & \ldots & \vdots & \vdots \\0 & 0 & 0 & \ldots & 0 & 1 \\1 & 0 & 0 & \ldots & 0 & 1 \\0 & 1 & 0 & \ldots & 0 & 1 \\\vdots & \vdots & \vdots & \ldots & \vdots & \vdots \\0 & 0 & 0 & \ldots & 1 & 1 \\1 & 0 & 0 & \ldots & 0 & 2 \\\vdots & \vdots & \vdots & \ldots & \vdots & \vdots \\0 & 0 & 0 & \ldots & 1 & {N_{V} - 1}\end{bmatrix}},{z = {\left. \begin{bmatrix}{\ln\left( w_{1} \right)} \\\vdots \\{\ln\left( w_{N_{H}} \right)} \\{j\frac{2\pi}{\lambda}d_{v}\cos\;\theta_{0}}\end{bmatrix}\Rightarrow z \right. = {\left( {A^{T}A} \right)^{- 1}A^{T}{{\ln({vr})}.}}}}$

The PMI module 622 then provides the estimated coefficients of lineartransmit antenna weights w₁, w₂, . . . , w_(N) _(H) (as indicated atarrow 630) to the vector quantizer 624 and the estimated vertical phaseshift parameter d_(v) cos θ₀ (as indicated at arrow 632) to the scalarquantizer 626.

The vector quantizer 624 quantizes the vector[w ₁, . . . ,w_(N) _(H) ]^(T)using the N_(H)−Tx antenna LTE codebook or any other codebook (e.g., aWiMax codebook) known to both the UE 611 and the eNodeB 610, and sendsan index 634 corresponding to an optimal codeword in the codebook to theeNodeB 610.

The scalar quantizer 626 quantizes

$\frac{2\pi}{\lambda}d_{v}\cos\;\theta_{0}$using scalar quantizing values known to both the UE 611 and the eNodeB610, and sends an index 636 corresponding to an optimal level to theeNodeB 610.

At the eNodeB 610, the vector dequantizer 616 uses the index 634 toselect the optimal codeword in the codebook to obtain[w ₁ , . . . ,w _(N) _(H) ]^(T),which the vector dequantizer 616 provides (as indicated at arrow 638) tothe PMI reconstructor 614.

Also at the eNodeB 610, the scalar dequantizer 618 uses the indexcorresponding to the optimal level to obtaind _(v) cos θ₀.which the scale dequantizer 618 provides (as indicated at arrow 640) tothe PMI reconstructor 614.

Based on the information from the vector dequantizer 616 and the scalardequantizer 618, the PMI reconstructor 614 of the eNodeB 610reconstructs the PMI vector in the form:

$\begin{bmatrix}{w_{1},\ldots\mspace{14mu},{w_{N_{H},}{\mathbb{e}}^{j\frac{2\;\pi}{\lambda}d_{v}\cos\;\theta_{0}}w_{1}},\ldots\mspace{14mu},{{\mathbb{e}}^{j\frac{2\;\pi}{\lambda}d_{v}\cos\;\theta_{0}}w_{N_{H}}},\ldots\mspace{14mu},} \\{{{\mathbb{e}}^{{j{({N_{V} - 1})}}\frac{2\pi}{\lambda}d_{v}\cos\;\theta_{0}}w_{1}},\ldots\mspace{14mu},{{\mathbb{e}}^{{j{({N_{V} - 1})}}\frac{2\pi}{\lambda}d_{v}\cos\;\theta_{0}}w_{N_{H}}}}\end{bmatrix}^{T},$

The PMI reconstructor 614 provides (as indicated at arrow 642) thereconstructed PMI vector to the precoder/transmitter 612 for use indownlink data transmission to the UE 611. For example, in single-userMIMO, the eNodeB 610 may use the reconstructed PMI vector to pre-codethe next downlink data to be sent to the UE 611. In multi-user MIMO,however, the PMI constructor 614 reconstructs a plurality of PMI vectorsfrom data received from respective UEs. Then, depending on thebeamforming scheme, the eNodeB 610 calculates new pre-coding matrices tocancel or reduce interference between the multiple users.

FIG. 7 is a flowchart of a method 700 for channel information feedbackin a MIMO network with 3D beamsteering according to one embodiment. Themethod 700 includes receiving 710 channel information from an eNodeB andcalculating 712 a first codebook index for a horizontal beamsteeringportion of the channel information. Calculating the first codebook indexincludes, according to certain embodiments, performing vectorquantization on the horizontal beamsteering portion of the channelinformation. The method 700 further includes calculating 714 a secondcodebook index for a vertical beamsteering portion of the channelinformation. Calculating the second codebook index includes, accordingto certain embodiments, performing scalar quantization of a parameterassociated with a vertical steering angle. The method 700 also includesproviding 716, as feedback, the first codebook index and the secondcodebook index.

FIG. 8 is a flowchart of a method 800 for 3D beamforming in atransmitter station with a 2D antenna array according to one embodiment.The method 800 includes receiving 810 a first feedback indicator from aUE and dequantizing 812 the first feedback indicator to determinecoefficients of linear transmit antenna weights to apply to respectivecolumns of antennas in the 2D antenna array. The method 800 furtherincludes dequantizing 814 the second feedback indicator to determinevertical phase shift parameters to apply to respective rows of theantennas in the 2D antenna array.

FIG. 9 provides an example illustration of the mobile device, such as aUE, a mobile station (MS), a mobile wireless device, a mobilecommunication device, a tablet, a handset, or other type of mobilewireless device that may be used with certain embodiments disclosedherein. The mobile device can include one or more antennas configured tocommunicate with transmission station, such as a base station (BS), anevolved Node B (eNB), a base band unit (BBU), a remote radio head (RRH),a remote radio equipment (RRE), a relay station (RS), a radio equipment(RE), or other type of wireless wide area network (WWAN) access point.The mobile device can be configured to communicate using at least onewireless communication standard including 3GPP LTE, WiMAX, High SpeedPacket Access (HSPA), Bluetooth, and WiFi. The mobile device cancommunicate using separate antennas for each wireless communicationstandard or shared antennas for multiple wireless communicationstandards. The mobile device can communicate in a wireless local areanetwork (WLAN), a wireless personal area network (WPAN), and/or a WWAN.

FIG. 9 also provides an illustration of a microphone and one or morespeakers that can be used for audio input and output from the mobiledevice. The display screen may be a liquid crystal display (LCD) screen,or other type of display screen such as an organic light emitting diode(OLED) display. The display screen can be configured as a touch screen.The touch screen may use capacitive, resistive, or another type of touchscreen technology. An application processor and a graphics processor canbe coupled to internal memory to provide processing and displaycapabilities. A non-volatile memory port can also be used to providedata input/output options to a user. The non-volatile memory port mayalso be used to expand the memory capabilities of the mobile device. Akeyboard may be integrated with the mobile device or wirelesslyconnected to the mobile device to provide additional user input. Avirtual keyboard may also be provided using the touch screen.

Some of the infrastructure that can be used with embodiments disclosedherein is already available, such as general-purpose computers, mobilephones, computer programming tools and techniques, digital storagemedia, and communications networks. A computing device may include aprocessor such as a microprocessor, microcontroller, logic circuitry, orthe like. The computing device may include a computer-readable storagedevice such as non-volatile memory, static random access memory (RAM),dynamic RAM, read-only memory (ROM), disk, tape, magnetic, optical,flash memory, or other computer-readable storage medium.

Various aspects of certain embodiments may be implemented usinghardware, software, firmware, or a combination thereof. A component ormodule may refer to, be part of, or include an application specificintegrated circuit (ASIC), an electronic circuit, a processor, (shared,dedicated, or group) and/or memory (shared, dedicated or group) thatexecute one or more software or firmware programs, a combinational logiccircuit, and/or other suitable components that provide the describedfunctionality. As used herein, a software module or component mayinclude any type of computer instruction or computer executable codelocated within or on a non-transitory computer-readable storage medium.A software module or component may, for instance, comprise one or morephysical or logical blocks of computer instructions, which may beorganized as a routine, program, object, component, data structure,etc., which performs one or more tasks or implements particular abstractdata types.

In certain embodiments, a particular software module or component maycomprise disparate instructions stored in different locations of acomputer-readable storage medium, which together implement the describedfunctionality of the module or component. Indeed, a module or componentmay comprise a single instruction or many instructions, and may bedistributed over several different code segments, among differentprograms, and across several computer-readable storage media. Someembodiments may be practiced in a distributed computing environmentwhere tasks are performed by a remote processing device linked through acommunications network.

Although the foregoing has been described in some detail for purposes ofclarity, it will be apparent that certain changes and modifications maybe made without departing from the principles thereof. It should benoted that there are many alternative ways of implementing both theprocesses and apparatuses described herein. Accordingly, the presentembodiments are to be considered illustrative and not restrictive, andthe invention is not to be limited to the details given herein, but maybe modified within the scope and equivalents of the appended claims.

Those having skill in the art will appreciate that many changes may bemade to the details of the above-described embodiments without departingfrom the underlying principles of the invention. The scope of thepresent invention should, therefore, be determined only by the followingclaims.

The invention claimed is:
 1. A user equipment (UE) for communication ina multiple-input multiple-output (MIMO) network, the UE comprising: achannel estimator to estimate channel information based on downlinkreference signals received from an evolved Node B (eNodeB); a vectorquantizer to quantize a first portion of the channel information using acodebook; a scalar quantizer to quantize a second portion of the channelinformation based on a vertical angle of a radio frequency (RF) beamtransmitted by the eNodeB; and a pre-coding matrix indicator (PMI)module to calculate a PMI vector based on the estimated channelinformation, the PMI vector comprising coefficients of linear transmitantenna weights for steering the RF beam at the eNodeB in a horizontaldirection, and wherein one or more of the coefficients of the PMI vectorare multiplied by a vertical phase shift parameter based on steering theRF beam at the eNodeB in to the vertical angle; wherein the verticalphase shift parameter is of the form:${\mathbb{e}}^{j\frac{2\;\pi}{\lambda}d_{v}\cos\;\theta_{0}},$ where λis a wavelength of the downlink reference signals, d_(V) is a verticaldistance between antennas in a two-dimensional (2D) antenna array at theeNodeB, and θ₀ is the vertical angle.
 2. The UE of claim 1, wherein thePMI vector is based on a feedback codebook for three-dimensional (3D) RFbeamsteering.
 3. The UE of claim 1, wherein the channel estimator isconfigured to estimate a channel matrix based on the received referencesignals, and wherein the PMI module is configured to calculate the PMIvector by performing singular value decomposition (SVD) on the estimatedchannel matrix and finding a number r of dominant eigenvectors, wherethe number r is a transmission rank.
 4. The UE of claim 1, wherein thePMI module is configured estimate an optimal set of the coefficients andthe vertical phase shift parameter.
 5. The UE of claim 1, wherein thescalar quantizer is configured to quantize the term:d _(v) cos θ₀ using a scalar quantizer known to both the UE and theeNodeB.
 6. The UE of claim 1, wherein the codebook used by the vectorquantizer comprises an N_(H) transmit antenna codebook of a thirdgeneration partnership project (3GPP) long term evolution (LTE) or LTEadvance (LTE-A) network, where N_(H) is a number of antennas arrangedhorizontally in a two-dimensional (2D) antenna array at the eNodeB. 7.The UE of claim 1, wherein the UE is configured to connect to at leastone of a wireless local area network (WLAN), a wireless personal areanetwork (WPAN), and a wireless wide area network (WWAN), and the UEincludes an antenna, a touch sensitive display screen, a speaker, amicrophone, a graphics processor, an application processor, internalmemory, a non-volatile memory port, or combinations thereof.
 8. The UEof claim 4, wherein the PMI module is configured to perform a leastsquares calculation to obtain the estimate.
 9. A method for channelinformation feedback in a multiple-input multiple-output (MIMO) networkwith three-dimensional beamsteering, the method comprising: receivingchannel information from an evolved Node B (eNodeB); calculating a firstcodebook index for a horizontal beamsteering portion of the channelinformation; calculating a second codebook index for a verticalbeamsteering portion of the channel information, wherein calculating thesecond codebook index comprises scalar quantization of a parameterassociated with a vertical steering angle, and wherein the parameterassociated with the vertical steering angle is of the form:${\mathbb{e}}^{j\frac{2\;\pi}{\lambda}d_{v}\cos\;\theta_{0}},$ where λis wavelength of the downlink reference signals, d_(V) is a verticaldistance between antennas in a two-dimensional (2D) antenna array at theeNodeB, and θ₀ is the vertical steering angle; and providing, asfeedback, the first codebook index and the second codebook index to theeNodeB.
 10. The method of claim 9, wherein calculating the firstcodebook index comprises vector quantization.
 11. The method of claim 9,wherein the vector quantization uses an N_(H) transmit antenna codebookof a third generation partnership project (3GPP) long term evolution(LTE) or LTE advance (LTE-A) network, where N_(H) is a number ofantennas arranged horizontally in a two-dimensional (2D) antenna arrayat the eNodeB using an LTE codebook.
 12. The method of claim 9, wherethe scalar quantization quantizes the term d_(v) cos θ₀.